Today with the help of emerging technologies scientists can gather data in many sectors which includes the Healthcare sector. The amount of data generated by machines and humans is overwhelming and is growing faster than it has ever had before. Taking advantage of all the power that exist in that data we have come up with a novel idea where we have used the development of machine learning techniques in diagnosing cardiovascular disease. Here, we fit a function to examples and using the function to generalize and make predictions about new diagnosis. In other words, the machine learning models learn from past data to make predictions about a patient diagnosis. This research provides a detailed work with the application of planning techniques is used in order to diagnose CVDs. A combination of biological data and medical imaging has been used. Ultimately, as this is a challenging research area open issues and its possible future works have also been discussed.